Junior Data & Automation Engineer

Engagement Context

The candidate will be expected to support a pre-existing technical environment that may include:

· A search and analytics platform in the ELK / OpenSearch family, fed by structured ingestion pipelines.

· A low-code workflow automation layer used for business and operational workflows.

· Internally developed Python services and AI-assisted agents integrated with third-party SaaS APIs.

Data Pipeline & Search Platform Support

· Monitor the health of ingestion pipelines from relational data sources into the search platform; identify backpressure, stalled jobs, and mapping or schema issues.

· Reprocess failed batches and support recovery from dead-letter queues.

· Assist with index lifecycle management, templates, and routine cluster-health checks.

· Support incremental changes to dashboards and visualizations, including new fields, metric fixes, and cosmetic updates.

· Raise capacity and performance concerns to the senior engineer before they become incidents.

Workflow Automation Support

· Monitor scheduled and event-driven workflow executions; triage failures and retry as appropriate.

· Apply small to medium changes, including updated templates, new data fields, credential refreshes, and webhook endpoint rotations.

· Maintain workflow stability when upstream third-party APIs change behavior.

· Track queue depth, rate-limit handling, and idempotent retry behavior.

Python Services & AI-Assisted Workflows

· Monitor execution logs, error rates, and usage metrics of internal Python services and AI-assisted workflows.

· Troubleshoot data ingestion into internal knowledge and retrieval systems.

· Apply tested configuration or prompt adjustments under senior review.

· Track and report on operational cost anomalies, including API usage and compute.

General Engineering & Documentation

· Write and maintain runbooks and known-good recovery procedures for every recurring incident class.

· Keep a clean changelog of production changes via pull requests where applicable.

· Participate in change windows and post-incident reviews.

· Escalate complex issues with clear, structured diagnostic context, including logs, timestamps, and reproduction steps.

Requirements

Must-Have Experience (1-3 years)

· Working experience with the ELK / OpenSearch family, such as Elasticsearch, OpenSearch, Kibana, OpenSearch Dashboards, Logstash, or equivalent, with at least one of them used in a real environment.

· Working experience with at least one low-code or workflow automation platform, such as n8n, Make, Zapier, Node-RED, Apache Airflow, or equivalent.

· Comfortable with a relational database, such as PostgreSQL, MySQL, or similar: able to read schemas, write SELECT queries, and investigate data issues.

· Comfortable on Linux: shell, SSH, log inspection, and process/service management.

· Docker basics: running containers, reading compose files, and inspecting logs.

· Reads and writes JSON and YAML fluently.

· Able to read and modify existing Python and JavaScript / Node.js code. The candidate is not expected to design services from scratch.

· REST API fluency: curl or Postman, headers, bearer tokens, pagination, rate-limit semantics, and webhooks.

· Git fundamentals: branches, commits, pull requests, and resolving simple merge conflicts.

· Structured troubleshooting: isolates variables, reads stack traces, bisects failures, and documents findings.

· Exposure to any commercial LLM API or vector database.

· Familiarity with common business SaaS APIs, including CRM, email, messaging, or data-enrichment platforms.

· Prior exposure to a data-engineering, operations, analytics, or security domain.